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Data Management & Oversight

Missing-Information Detection Agent

H1ST-AI-DEN-002 · Task 2.1

The gaps you find at lock should surface now

The missing value you catch at database lock is the one that slips your timeline; the same gap caught today is a quick query. The Missing-Information Detection Agent runs template completeness analysis against your expected CRF structure, uses pattern recognition to spot gaps that simple required-field checks miss, and drafts targeted, context-aware queries so sites know exactly what to supply the first time.

The grind you know

The gaps you find at lock should surface now

Missing data is the query you raise more than any other, and it has a cruel habit of showing up late — sometimes not until you're trying to lock the database. Manual completeness review simply can't keep pace with enrollment, and when the best you can send is a generic 'this field is blank,' you leave sites guessing at what you actually need — and waiting through another round-trip to find out.

Part of the Clinical Data Capture family

Source-document extraction & query automation.

The missing value you catch at database lock is the one that slips your timeline; the same gap caught today is a quick query. The Missing-Information Detection Agent runs template completeness analysis against your expected CRF structure, uses pattern recognition to spot gaps that simple required-field checks miss, and drafts targeted, context-aware queries so sites know exactly what to supply the first time.

  • CDASH
  • HIPAA
  • 21 CFR Part 11
Explore the Clinical Data Capture family

How it works

  1. 1

    Load the expected structure

    Point the agent at the CRF template and visit schedule so it knows what a complete record looks like for each form.

  2. 2

    Detect the gaps

    It compares submitted data to the expected fields and applies pattern recognition to surface both hard and inferred missing items.

  3. 3

    Generate queries

    For each confirmed gap it drafts a context-aware query, ready for a data manager to approve and route to the site.

Capabilities

What it takes off your plate

Template completeness analysis

Compares each submitted record against the expected field set for that visit and form, accounting for conditional and skip logic so it only flags fields that should be present.

Pattern-based gap detection

Uses pattern recognition across the dataset to catch gaps that a static required-field rule misses — an unrecorded assessment implied by a related result, or a visit with a suspiciously sparse form.

Context-aware query generation

Drafts a specific, plain-language query per gap that names the missing item and its visit context, so sites respond with the right value instead of asking for clarification.

Safe Harbor de-identification

Removes all 18 HIPAA Safe Harbor identifiers before any record enters completeness review, keeping PHI out of the query layer.

What you get

  • Completeness report by subject, visit, and form
  • Context-aware query drafts ready for the EDC query workflow
  • Prioritized gap list ranked by data criticality
  • De-identified working dataset (Safe Harbor)

In practice

What this looks like on a real study

Where the agent shows up in the day-to-day of a live trial — the moments the grind usually lives in.

A gap you'd only find at lock

An unrecorded assessment is the kind of gap that usually surfaces when you're trying to lock the database. Template completeness analysis catches it now, against the expected field set for that visit and form, while it is still a quick query rather than a timeline risk.

Skip logic wrongly flagged as blank

You don't want a completeness check nagging sites about fields that are correctly not applicable. The analysis respects conditional and skip logic, so it only flags fields that genuinely should be present for that record.

A generic 'this field is blank' query

When the best you can send is a vague blank-field notice, the site guesses and you wait through another round-trip. The agent drafts a context-aware query that names the missing item and its visit context, so the site supplies the right value the first time.

Proof

The impact on your study

95%
Missing required fields detected
90%
Response-to-update accuracy
100%
PHI removal

Figures shown are pre-launch targets based on internal benchmarks, not guaranteed outcomes.

Works with your stack

  • Medidata Rave

    EDC

  • Oracle Clinical

    EDC

  • Veeva Vault

    EDC

Who it's for

Built for the teams who run trials

More from Data Management & Oversight

Peace of mind

Built to the standards inspectors expect

Every output is generated inside a validated, audit-ready platform, kept under human-in-the-loop control, and mapped to the regulatory and CDISC standards this agent supports.

  • CDASH
  • HIPAA
  • 21 CFR Part 11

Frequently asked questions

See the Missing-Information Detection Agent on your study

Walk through it on your own workflow with a clinical-trials expert — no pressure, no obligation, and honest answers, including on the limits.